Application of indole-3-propionic acid as biomarker in early warning of cognitive impairment after stroke

Abstract

The invention discloses an application of indole-3-propionic acid as a biomarker in early warning of cognitive impairment after stroke. According to the application disclosed by the invention, the indole-3-propionic acid is confirmed as the biomarker of cognitive impairment after stroke through large-scale screening, and the indole-3-propionic acid belongs to a biomarker of a metabolite type, so that noninvasive sampling is facilitated, content fluctuation in a body can appear in a short time after stroke, and the cognitive impairment can be identified. The risk degree of cognitive impairment can be obtained by detecting within three months after stroke, the time node is earlier than that of conventional clinical diagnosis, and timely discovery and treatment are facilitated.

Description

Technical Field

[0001] This application relates to the field of clinical diagnostic technologies. Specifically, this application relates to the use of indole-3-propionic acid as a biomarker for early warning of post-stroke cognitive impairment. Background Art

[0002] Post-stroke cognitive impairment is a common complication among stroke survivors, seriously affecting the quality of life and rehabilitation process of patients. Currently, the predictive methods for post-stroke cognitive impairment are relatively limited, mainly relying on clinical assessment scales and neuroimaging examinations, etc. However, these methods have certain subjectivity and lag, and it is difficult to accurately predict in the early stage of the disease. Summary of the Invention

[0003] In view of the shortcomings of the existing methods, this application proposes the use of indole-3-propionic acid as a biomarker for early warning of post-stroke cognitive impairment to solve the technical problems of lagging predictive results and insufficient objectivity of predictive results in related technologies.

[0004] This application provides the use of indole-3-propionic acid as a biomarker for early warning of post-stroke cognitive impairment.

[0005] Optionally, non-targeted metabolomics is used for screening and targeted metabolomics is used for confirmation that indole-3-propionic acid is one of the biomarkers for post-stroke cognitive impairment.

[0006] Furthermore, the early warning of post-stroke cognitive impairment is carried out within 3 months after the occurrence of the stroke.

[0007] Even further, the object of the early warning of post-stroke cognitive impairment is patients with ischemic stroke.

[0008] Optionally, the early warning includes the following steps: Obtain samples of stroke patients, where the samples include blood samples and / or fecal samples; Detect the content of indole-3-propionic acid in the blood samples and / or fecal samples; Based on a pre-constructed prediction model, confirm the risk degree of cognitive impairment in the stroke population.

[0009] Optionally, the detection of the content of indole-3-propionic acid in the blood samples and / or fecal samples includes quantitatively detecting the content of indole-3-propionic acid by using high performance liquid chromatography, high performance liquid chromatography-tandem mass spectrometry, gas chromatography or enzyme-linked immunosorbent assay.

[0010] Optionally, the steps for constructing the prediction model include: Obtain grouped data of those with cognitive impairment and grouped data of those without cognitive impairment in the stroke population; Compare and analyze the differences in the content of indole-3-propionic acid between the two groups, as well as the correlation between the difference situation and the scores of the cognitive assessment scale, to clarify the quantitative relationship between the decrease in the content of indole-3-propionic acid and the occurrence of post-stroke cognitive impairment; Based on the correlation data obtained between the content of indole-3-propionic acid and cognitive impairment, combined with the clinical information of each patient in the stroke population, use statistical and / or machine learning methods to construct a prediction model for post-stroke cognitive impairment.

[0011] Optionally, the comparison and analysis of the differences in the content of indole-3-propionic acid between the two groups includes respectively obtaining samples of stroke patients and stroke mice, screening by non-targeted metabolomics and confirming indole-3-propionic acid as one of the biomarkers for post-stroke cognitive impairment by targeted metabolomics.

[0012] Further optionally, the stroke mice include a middle cerebral artery stroke model established by the suture method.

[0013] Optionally, the comparison and analysis of the differences in the content of indole-3-propionic acid between the two groups includes performing a significant difference analysis using an independent samples t-test or a Mann-Whitney U test.

[0014] Optionally, the correlation between the content of indole-3-propionic acid and the scores of the cognitive assessment scale is analyzed by linear regression.

[0015] The beneficial technical effects brought by the technical solutions provided in the embodiments of the present application include: (1) The application of the present application confirms indole-3-propionic acid as a biomarker for post-stroke cognitive impairment through large-scale screening. Indole-3-propionic acid belongs to a metabolite-type biomarker, which is convenient for non-invasive sampling and can also show fluctuations in its content in the body within a short time after stroke. Detecting within 3 months after stroke can obtain the risk degree of cognitive impairment, which is earlier than the conventional clinical diagnosis time point and is conducive to timely detection and treatment.

[0016] (2) The application of the present application pre-constructed a prediction model with a relatively high accuracy, considering multiple factors comprehensively, and confirmed the reliability of indole-3-propionic acid as a biomarker for post-stroke cognitive impairment from another aspect.

[0017] The additional aspects and advantages of the present application will be partially given in the following description, which will become obvious from the following description, or can be understood through the practice of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] The above and / or additional aspects and advantages of the present application will become obvious and easy to understand from the following description of the embodiments in conjunction with the drawings, in which: Figure 1 The serum metabolic profiles of the Sham group and the middle cerebral artery ischemia-reperfusion (MCAO) group provided by the embodiments of the present application on the 3rd day after stroke; Figure 2 The goodness of fit (R²) and predictive ability (Q²) of the OPLS-DA model provided by the embodiments of the present application to verify the differences in microbial communities between the Sham group and the MCAO group. The model shows strong separation ability and reliability; Figure 3 The result graph of comparing 5 metabolites significantly up-regulated and down-regulated in the serum between the Sham group and the MCAO group provided by the embodiments of the present application; Figure 4 The statistical chart of the differences between the group with post-stroke cognitive impairment and the group without post-stroke cognitive impairment provided by the embodiments of the present application; Figure 5 The linear regression analysis graph between IPA and MOCA scores provided by the embodiments of the present application; Figure 6 The accuracy evaluation graph of the prediction model provided by the embodiments of the present application; Figure 7 The statistical chart of IPA levels in patients with post-stroke cognitive impairment and patients with normal cognition three months after stroke provided by the embodiments of the present application; Figure 8 The result of reducing the infarct area by IPA intervention provided by the embodiments of the present application; Figure 9 The result of improving post-stroke cognitive ability by intraperitoneal injection of IPA provided by the embodiments of the present application; Figure 10 The result of examining that IPA can cross the blood-brain barrier by intraperitoneal injection provided by the embodiments of the present application; Figure 11 The result of improving post-stroke cognitive ability by intracerebroventricular injection of IPA provided by the embodiments of the present application. Detailed implementation manners

[0019] The embodiments of the present application will be described below with reference to the accompanying drawings in the present application. It should be understood that the implementation manners described below in conjunction with the accompanying drawings are exemplary descriptions for explaining the technical solutions of the embodiments of the present application, and do not constitute limitations on the technical solutions of the embodiments of the present application.

[0020] Those skilled in the art can understand that, unless specifically stated, the terms "the" and "said" used herein may also include the plural form. It should be further understood that the term "including" used in the specification of the present application means the presence of the described features, integers, steps, operations, elements, and / or components, but does not exclude the presence of other features, information, data, steps, operations, elements, components, and / or combinations thereof supported by the art. The term "and / or" used herein means at least one of the items defined by the term. For example, "A and / or B" can be implemented as "A", or "B", or "A and B".

[0021] To make the objectives, technical solutions, and advantages of the present application clearer, the embodiments of the present application will be further described in detail below with reference to the accompanying drawings.

[0022] Post-Stroke Cognitive Impairment (PSCI) is a common complication after stroke. The onset time varies from person to person, but generally follows the following pattern: Acute-phase screening (1-2 weeks after stroke): Doctors will conduct a preliminary cognitive assessment within 1-2 weeks after stroke to predict whether the patient is likely to develop PSCI. This step is crucial because early intervention can significantly improve the prognosis.

[0023] Formal diagnosis (3-6 months after stroke): The definition of PSCI clearly requires that cognitive impairment persists until 6 months after stroke. In clinical practice, if a patient shows a decline in cognitive function within 3-6 months after stroke and meets the diagnostic criteria, they can be diagnosed with PSCI.

[0024] The assessment and diagnosis of PSCI is a multi-dimensional and phased process that requires comprehensive judgment combining clinical, imaging, and neuropsychological aspects. Early screening (acute phase) and systematic assessment (recovery phase) are the keys to diagnosis. At the same time, other etiologies need to be excluded to ensure the pertinence of treatment. It can be seen that the process of diagnosing PSCI is long and it is difficult to make an early diagnosis, which affects prevention and treatment after diagnosis.

[0025] In recent years, the research on the relationship between the gut microbiota and human health has become increasingly in-depth. The gut microbiota participates in various physiological processes of the host through its metabolites, including immune regulation, nerve signal conduction, etc. After stroke, the biodiversity of the gut microbiota is disordered, and the types of probiotics such as Lactobacillaceae ( Lactobacillaceae ), and Akkermansia ( Akkermansia) has been shown to hinder neurological recovery, especially in the acute phase. Disruption of intestinal microbial composition is also associated with worsening cognitive outcomes in stroke patients. Increasing evidence highlights the role of microbial-derived metabolites in regulating central nervous system (CNS) function and pathology. Through large-scale screening, this application found that indole-3-propionic acid, as an important metabolite of intestinal flora, changes significantly in stroke patients, but its changes in patients with post-stroke cognitive impairment have not been fully explored and utilized. Previous studies have found that the metabolic profiles of intestinal flora in patients with stroke cognitive impairment and mouse models of stroke cognitive impairment are significantly disordered. However, intestinal flora metabolites associated with the occurrence of stroke cognitive impairment remain to be identified, and the use of this key metabolite as a preventive and therapeutic technology for stroke cognitive impairment has not yet been developed.

[0026] The indole-3-propionic acid of this application was confirmed after non-targeted metabolomics screening. Non-targeted metabolomics is a global analysis method of metabolites without preset targets. It uses technologies such as liquid chromatography-mass spectrometry (LC-MS), gas chromatography-mass spectrometry (GC-MS) or nuclear magnetic resonance (NMR) to perform high-throughput scanning of all detectable small molecule metabolites (molecular weight is usually less than 1000 Da) in biological samples (such as cells, tissues, body fluids), aiming to discover metabolic changes associated with physiological or pathological states, reveal potential biomarkers or metabolic pathways, and is suitable for global exploration of indications.

[0027] The following is a detailed description of the early warning method for post-stroke cognitive impairment based on indole-3-propionic acid.

[0028] Non-targeted metabolomics was used to detect serum metabolic profiles. Mice were first used as experimental subjects. The serum samples of mice were placed on ice for cooling, then centrifuged at 3000 g for 5 minutes at 4°C, and the fragments or lipid layers were separated using a Microfuge 20R centrifuge (BeckmanCoulter, USA). Each 50 μL sample aliquot was mixed with 150 μL of acetonitrile and vortexed for 30 seconds. Then centrifuged at 14,000 g for 20 minutes at 4°C, and 180 μL of supernatant was carefully transferred to a new 1.5 mL tube and blown dry with nitrogen. The residue was re-dissolved with 50 μL of 50% acetonitrile (water: acetonitrile = 1:1) and centrifuged at 15,800 g for 15 minutes. In order to optimize and verify the chromatographic and TOFMS conditions, a composite "quality control" was prepared: For each sample, 5 μL of the aliquot was taken and separated using a Waters ACQUITY HSS T3 C18 column (100 mm × 2.1 mm i.d., 1.7 μm). The column temperature was maintained at 50°C, and a Vanquish ultra-high performance liquid chromatograph (Thermo Fisher Scientific) was used. The mobile phase consisted of 0.1% formic acid aqueous solution (phase A) and acetonitrile (phase B), with a flow rate of 0.4 mL / min. The following gradient program was adopted: phase B was linearly increased from 3% to 10% (0 - 1 minute), from 10% to 40% (1 - 3 minutes), from 40% to 70% (3 - 9 minutes), from 70% to 80% (9 - 18 minutes), from 80% to 95% (18 - 20 minutes), 95% of phase A was maintained for 3 minutes, and then returned to 3% of phase B and maintained for 3 minutes. Full scan and fragmentation analysis were performed using a high-resolution Exploris 240 Orbitrap mass spectrometer from Thermo Fisher Scientific. The global operating parameters included: the spray voltage was set to 3500 V in the HESI positive mode and 3000 V in the negative mode; the transfer line temperature was set to 320°C, and the evaporator temperature was 300°C; the sheath gas, auxiliary gas, and sweep gas flow rates were set to 40, 10, and 1 Arb, respectively. Top-5 data-dependent acquisition (DDA) was performed, with a scan range of 50 - 750 m / z and MS1 resolution.

[0029] As Figures 1 - 3 shown, (A) Serum metabolic profiles of the Sham group and the MCAO (Middle Cerebral Artery Occlusion) group on the 3rd day after stroke. (B) OPLS-DA model validation showed the goodness of fit (R²) and predictive ability (Q²) of the differences in the microbial communities between the Sham group and the MCAO group. The model showed strong separation ability and reliability. (C) Comparison of the 5 metabolites significantly upregulated and downregulated in the serum between the Sham group and the MCAO group.

[0030] By processing the serum samples of the stroke model mice and normal mice in the above manner and analyzing the collected sample data according to non-targeted metabolomics, it was confirmed that there was a significant correlation between the decrease in the content of indole-3-propionic acid and the occurrence of post-stroke cognitive impairment.

[0031] Furthermore, validation was carried out in the stroke population. Blood samples of 100 stroke patients (50 with cognitive impairment and 50 without cognitive impairment) were collected in the experiment, and the content of indole-3-propionic acid was detected by high performance liquid chromatography. As Figures 4 - 6 shown, the data of the patient group with cognitive impairment was significantly positively correlated with the MoCA score (correlation coefficient r = 0.6, P < 0.01).

[0032] Three months later, the IPA content in patients with post-stroke cognitive impairment was significantly lower than that in stroke patients with normal cognition (as Figure 7 shown). At 3 months after stroke, patients with post-stroke cognitive impairment and stroke patients with normal cognition were followed up, and blood samples were collected.

[0033] Detection by high performance liquid chromatography (HPLC): Sample pretreatment: The blood samples were centrifuged, the supernatant was taken, extracted with an appropriate organic solvent (such as methanol), and centrifuged and filtered for later use.

[0034] Chromatographic condition setting: A C18 reverse phase chromatographic column was used, the mobile phase was a methanol-water mixed system, the flow rate was set at 1.0 mL / min, and the detection wavelength was 280 nm.

[0035] Standard curve drawing: A series of indole-3-propionic acid standard solutions with different concentrations were prepared, injected into the chromatograph, and the standard curve was drawn with the concentration as the abscissa and the peak area as the ordinate.

[0036] Sample detection: The processed samples were injected into the chromatograph, and the content of indole-3-propionic acid in the samples was calculated according to the standard curve.

[0037] Annotation of metabolites was performed by comparing the retention index and mass spectrometry data with reference standards of known structures in the JiaLib metabolite database using ChromaTOF software. The data set was analyzed by orthogonal partial least squares discriminant analysis (OPLS-DA) in the R statistical environment (version 3.4.4). The ropls package in R language includes metrics such as R2 (goodness of fit) and Q2 (prediction performance), and a permutation test was performed. This analysis comprehensively evaluated the explanatory ability (R2) and prediction ability (Q2) of the model through cross-validation. To identify significant differential metabolites, the criteria were set as: variable importance in projection (VIP) > 1 and P value < 0.05.

[0038] Figure 4Statistical methods adopted: The independent samples t-test or Mann-Whitney U test (when the data does not conform to the normal distribution) is used to compare the differences between two groups. The independent samples t-test is a parametric test method used to compare whether there are significant differences in the means of two independent samples. It assumes that the data follows a normal distribution and the variances of the two groups are equal (homoscedasticity). Output indicators: t-value: A statistic measuring the difference in means between the two groups. p-value: If the p-value is less than the significance level (e.g., 0.05), the null hypothesis is rejected, indicating that there are significant differences in the means of the two groups. The Mann-Whitney U test is a non-parametric test method used to compare whether the distributions of two independent samples are the same, without relying on the normality assumption. It determines the median or distribution differences by comparing the ranks (sorting positions) of the two groups of data. Output indicators: U-value: A statistic reflecting the difference in the total ranks of the two groups, p-value: If the p-value is less than the significance level, the null hypothesis is rejected, indicating that the distributions of the two groups are different.

[0039] Figure 5 Pearson correlation analysis and linear regression analysis (Linear Regression) were used: The regression line in the figure represents the relationship between two variables, which may be modeled using linear regression, where the independent variable is the MoCA score and the dependent variable is a biomarker or other clinical indicator. The r-value and p-value are used to evaluate the goodness of fit and significance of the regression model (p < 0.05 usually indicates statistical significance).

[0040] Figure 6 Statistical methods: This part indicates that the study used a logistic regression prediction model for classification or regression analysis. The accuracy rate of the model is 80%, indicating the proportion of correct predictions of the model on the test set. The prediction accuracy is usually evaluated through cross-validation to avoid overfitting and improve generalization ability.

[0041]

[0042] The prediction accuracy of the prediction model constructed based on these data reached 80% in the independent validation set (including 30 patients), indicating that the present invention has good application prospects.

[0043] This application confirms that indole-3-propionic acid is a key metabolite for preventing post-stroke cognitive impairment, and further verifies that improving post-stroke cognitive impairment by targeting to increase the content of indole-3-propionic acid provides a new effective means for the prevention and treatment of post-stroke cognitive impairment.

[0044] Indole-3-propionic acid improves stroke injury.

[0045] Experimental verification methods in animals: Sample collection: Serum samples were collected from post-stroke mice and normal mice.

[0046] Detection by high performance liquid chromatography tandem mass spectrometry (LC / MSMS): Sample pretreatment: The blood samples were centrifuged, and the supernatant was taken. It was extracted with an appropriate organic solvent (such as methanol), centrifuged and filtered for later use.

[0047] Chromatographic condition setting: A C18 reversed-phase chromatographic column was used. The mobile phase was a methanol-water mixed system. The flow rate was set at 1.0 mL / min, and the detection wavelength was 280 nm.

[0048] Standard curve plotting: A series of standard solutions of indole-3-propionic acid (IPA), indoleacetic acid (IAA), and indolelactic acid (ILA) with different concentrations were prepared and injected into the chromatograph. The standard curve was plotted with the concentration as the abscissa and the peak area as the ordinate.

[0049] Sample detection: The processed samples were injected into the chromatograph, and the contents of IPA, ILA, and IAA in the samples were calculated according to the standard curve.

[0050] Preparation of animal model Grouping of mice: Male C57BL / 6J mice at 10 weeks of age were selected and randomly divided into a sham operation group (Sham) and a stroke group (Stroke).

[0051] Preparation of stroke model: A middle cerebral artery occlusion model (MCAO) was established by the suture method. The specific steps are as follows: Anesthesia of mice: The mice were anesthetized with a mixed gas of 2% isoflurane and 30% oxygen.

[0052] Neck incision: The skin was incised in the middle of the mouse neck, and the external carotid artery was isolated.

[0053] Insertion of nylon suture: A 4-0 nylon suture was inserted through the external carotid artery into the internal carotid artery to block the origin of the middle cerebral artery, causing focal cerebral ischemia.

[0054] Postoperative treatment: After the operation, the mice woke up in a warm environment, and their vital signs were monitored.

[0055] Drug intervention Intervention plan: Sham operation group: No intervention was carried out, and only conventional feeding was performed.

[0056] IPA group: After stroke modeling, intraperitoneal injection of IPA or IAA or ILA was immediately started at a dose of 20 mg / kg once a day for 3 consecutive days.

[0057] Control group: Immediately after stroke modeling, an equal volume of normal saline was injected intraperitoneally once a day for 3 consecutive days.

[0058] TTC staining Anesthetize the mice: Anesthetize the mice with a mixture of 2% isoflurane and 30% oxygen.

[0059] Remove the brain: After sacrificing the animals by decapitation, quickly remove the brain or heart (within 10 minutes), transfer it in 0 - 4°C PBS solution, and freeze it in a -20°C refrigerator for 30 minutes.

[0060] Sectioning: Section preparation: Cut the brain coronally into four 2 - mm sections, taking care not to damage the integrity of the brain slices. The first cut is made at the midpoint between the anterior end of the brain and the optic chiasm; the second cut is at the optic chiasm; the third cut is at the infundibular stalk; the fourth cut is between the infundibular stalk and the caudal end of the posterior lobe.

[0061] Staining: Staining solution: Place the brain slices in a 2% TTC solution (dissolved in PBS), put them in a 37°C incubator in the dark for 15 - 30 minutes, and turn the brain slices midway to make the staining uniform.

[0062] Observation and fixation: Photograph and observe: After staining, place the brain slices in a 4% formalin solution for fixation and preservation for subsequent quantitative photographing to detect the infarct area.

[0063] After stroke modeling in mice, they were divided into the IPA group and the control group, and intraperitoneal injection was carried out for 14 consecutive days, which could improve learning ability.

[0064] Experimental method: Animal model preparation: Intraperitoneal injection of IPA: Injection protocol: After stroke modeling, mice in the IPA group were intraperitoneally injected with IPA for 14 consecutive days, and the control group was injected with an equal volume of normal saline.

[0065] Dose: According to the results of the preliminary experiment, the injection dose of IPA was determined to be 20 mg / kg.

[0066] Learning ability assessment: Use the novel object recognition and Y - maze to detect the learning and memory abilities of mice. The test includes the place navigation test and the spatial exploration test.

[0067] Motor ability assessment: Use the open - field test and the rotarod test to detect the learning and memory abilities of mice. The test includes the movement distance and movement endurance.

[0068] After intraperitoneal injection of IPA, the IPA concentration in the brain was detected at 0 hour, 0.5 hour, and 6 hours.

[0069] Experimental method: Animal treatment: Grouping of mice: Male C57BL / 6J mice at 10 weeks of age were randomly divided into the IPA group and the control group.

[0070] Intraperitoneal injection of IPA: Mice in the IPA group were intraperitoneally injected with IPA, and the control group was injected with an equal volume of normal saline.

[0071] Sample collection: Time points: At 0 hour, 0.5 hour, and 6 hours after injection, the mice were sacrificed respectively, and brain tissues were taken.

[0072] Detection by high performance liquid chromatography (HPLC): After continuous intraventricular injection of IPA for 14 days in mice after stroke modeling, the learning ability can be improved Experimental method: Preparation of stroke model: The MCAO model was established by the suture method. After the mice were anesthetized, a 4-0 nylon suture was inserted into the internal carotid artery through the external carotid artery to block the origin of the middle cerebral artery, causing focal cerebral ischemia.

[0073] Intraventricular injection of IPA: Injection protocol: After stroke modeling, mice in the IPA group were continuously intraventricularly injected with IPA for 14 days, and the control group was injected with an equal volume of normal saline.

[0074] Dosage: According to the results of the preliminary experiment, the injection dosage of IPA was determined to be 10 uM, 5 μL.

[0075] Evaluation of learning ability: Behavioral test: The Morris water maze was used to test the learning and memory abilities of mice. The test included the place navigation test and the spatial exploration test.

[0076] Data recording: Record the time (latency) for the mice to find the platform and the time spent in the target quadrant.

[0077] The experimental results are as follows: Figure 8 : After stroke modeling in mice, they were divided into the IPA group and the control group, and intraperitoneally injected for 14 consecutive days to investigate the change in the area of cerebral infarction in mice.

[0078] (A-C) Levels of IPA, ILA, and IAA in the sera of the sham group (S) and the MCAO group (M) on the 3rd day. The in vivo contents of all three metabolites decreased significantly. (D) Infarct area in brain sections of MCAO mice treated with IPA, which was significantly reduced compared with the control group. (E) Infarct area in brain sections of MCAO mice treated with ILA, which showed no improvement compared with the control group. (F) Infarct area in brain sections of MCAO mice treated with IAA, which showed no improvement compared with the control group.

[0079] This demonstrated that IPA could reduce the infarct area in the brain after stroke.

[0080] Figure 9: Detection results of IPA concentration in the brain at different time points after intraperitoneal injection of IPA, revealing the distribution pattern of IPA in the brain and providing an important basis for determining its mechanism of action.

[0081] (A) Timeline of the behavioral test experiment. (B) Time spent in the novel arm. (C) Percentage of time exploring the novel object. (D) Walking distance in the open field. (E) Maximum speed in the rotarod test.

[0082] Figure 10 : After intraperitoneal injection of IPA, the change in IPA level in the brain tissue was detected, which demonstrated that intraperitoneal injection could cross the blood-brain barrier.

[0083] Figure 11 : After continuous 14-day intracerebroventricular injection of IPA in mice after stroke modeling, the experimental data showing improvement in learning ability indicated that intracerebroventricular injection of IPA was also an effective treatment method.

[0084] (A) Timeline of the behavioral test after intracerebroventricular injection. (B) Time spent in the novel arm in the Y-maze test. (C) Percentage of time exploring the novel object. (D) Walking distance in the open field. (E) Maximum speed in the rotarod test.

[0085] In summary, the above results showed that: 1. Animal model experiment: Male C57BL / 6J mice at 10 weeks of age were randomly divided into a sham operation group and a stroke group. After 3 days of modeling, metabolites in the sera were detected, and it was found that the content of indole-3-propionic acid in the sera of the stroke group mice decreased.

[0086] 2. Intraperitoneal injection of IPA improved stroke symptoms: After stroke modeling in mice, they were divided into an IPA group and a control group, and intraperitoneal IPA injection was performed continuously for 3 days. The results showed that the infarct area of the mice in the IPA group decreased.

[0087] 3. Long-term intraperitoneal injection of IPA improves learning ability: Mice were divided into a sham operation group, an IPA group after stroke, and a control group after stroke. Intraperitoneal injection was performed continuously for 14 days, and it was found that the learning ability of mice in the IPA group after stroke was improved.

[0088] 4. Study on the brain distribution of IPA: After intraperitoneal injection of IPA, the IPA concentration in the brain was detected at 0 hour, 0.5 hour, and 6 hours to study its distribution in the brain, providing a basis for determining its mechanism of action.

[0089] 5. Intraventricular injection of IPA improves learning ability: After stroke modeling in mice, intraventricular injection of IPA was performed continuously for 14 days. The results showed that this method could also improve the learning ability of mice.

[0090] 6. Population cohort study: Long-term follow-up was conducted on patients with post-stroke cognitive impairment and stroke patients with normal cognition. It was found that the IPA content in patients with post-stroke cognitive impairment was still significantly lower than that in stroke patients with normal cognition 3 months after onset, further confirming the close relationship between IPA and post-stroke cognitive impairment.

[0091] The present invention aims to solve the problem of predicting post-stroke cognitive impairment and provides a reliable molecular marker. Indole-3-propionic acid, as a metabolite of the human gut microbiota, shows specific change rules in patients with post-stroke cognitive impairment and is negatively correlated with the degree of cognitive impairment, and is expected to become a key indicator for accurately predicting this disease. The present invention belongs to the field of biomedical technology and focuses on developing disease prediction tools using human metabolites to assist in the early detection and intervention of post-stroke cognitive impairment.

[0092] In summary, the present application provides an application of indole-3-propionic acid as a biomarker in the early warning of post-stroke cognitive impairment. Further, an early warning method for post-stroke cognitive impairment based on indole-3-propionic acid includes the following steps: obtaining a sample of a stroke patient, the sample including a blood sample and / or a fecal sample; detecting the content of indole-3-propionic acid in the blood sample and / or the fecal sample; and confirming the risk degree of cognitive impairment in the stroke population based on a pre-constructed prediction model. The application of the present application confirms through large-scale screening that indole-3-propionic acid is a biomarker for post-stroke cognitive impairment. Indole-3-propionic acid belongs to a metabolite-type biomarker, which is convenient for non-invasive sampling and can also show fluctuations in its content in the body within a short time after stroke. By detecting within 3 months after stroke, the risk degree of cognitive impairment can be known, which is earlier than the conventional clinical diagnosis time point and is beneficial for timely discovery and treatment.

[0093] Those skilled in the art can understand that the various operations, methods, steps, measures, and solutions in the processes discussed in this application can be alternated, changed, combined, or deleted. Further, other steps, measures, and solutions in the various operations, methods, and processes discussed in this application can also be alternated, changed, rearranged, decomposed, combined, or deleted. Further, the steps, measures, and solutions in the related technologies that are the same as those disclosed in the various operations, methods, and processes in this application can also be alternated, changed, rearranged, decomposed, combined, or deleted.

[0094] The terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the quantity of the indicated technical features. Thus, features defined with "first" and "second" may explicitly or implicitly include one or more of such features. In the description of this application, unless otherwise specified, the meaning of "a plurality of" is two or more.

[0095] In the description of this specification, specific features, structures, materials, or characteristics may be combined in a suitable manner in any one or more embodiments or examples.

[0096] The above are only some embodiments of this application. It should be noted that for those of ordinary skill in the art, without departing from the technical concept of the solution of this application, using other similar implementation means based on the technical idea of this application also belongs to the protection scope of the embodiments of this application.

Claims

1. Use of indole-3-propionic acid as a biomarker in early warning of post-stroke cognitive impairment.

2. The application according to claim 1, characterized in that, Screen by non-targeted metabolomics and confirm indole-3-propionic acid as one of the biomarkers of post-stroke cognitive impairment by targeted metabolomics.

3. The application according to claim 1, characterized in that, The early warning of post-stroke cognitive impairment is carried out within 3 months after the occurrence of stroke.

4. The application according to claim 1, wherein The object of the early warning of post-stroke cognitive impairment is patients with ischemic stroke.

5. The application according to claim 1, characterized in that, The early warning includes the following steps: Obtain samples of stroke patients, and the samples include blood samples and / or fecal samples; Detect the content of indole-3-propionic acid in blood samples and / or fecal samples; Based on a pre-constructed prediction model, confirm the risk of cognitive impairment in stroke patients.

6. The application according to claim 5, characterized in that The detection of the content of indole-3-propionic acid in blood samples and / or fecal samples includes quantitatively detecting the content of indole-3-propionic acid by high performance liquid chromatography, high performance liquid chromatography-tandem mass spectrometry, gas chromatography or enzyme-linked immunosorbent assay.

7. The application according to claim 5, wherein The steps for constructing the prediction model include: Obtain grouped data of stroke patients with cognitive impairment and grouped data of those without cognitive impairment; Compare and analyze the differences in the content of indole-3-propionic acid between the two groups, and the correlation between the difference and the scores of cognitive assessment scales, so as to clarify the quantitative relationship between the decrease in the content of indole-3-propionic acid and the occurrence of post-stroke cognitive impairment; Based on the obtained correlation data between the content of indole-3-propionic acid and cognitive impairment, combined with the clinical information of each patient in the stroke population, use statistical and / or machine learning methods to construct a prediction model for post-stroke cognitive impairment.

8. The application according to claim 7, characterized in that, The comparison and analysis of the differences in the content of indole-3-propionic acid between the two groups includes respectively obtaining samples of the stroke population and stroke mice, screening by non-targeted metabolomics and confirming indole-3-propionic acid as one of the biomarkers of post-stroke cognitive impairment by targeted metabolomics.

9. The application according to claim 8, wherein The stroke mice include a middle cerebral artery stroke model established by the suture method.

10. The application according to claim 7, wherein The comparison and analysis of the differences in the content of indole-3-propionic acid between the two groups includes performing a significant difference analysis by independent samples t-test or Mann-Whitney U test.

11. The application according to claim 7, wherein The correlation between the content of indole-3-propionic acid and the scores of cognitive assessment scales is analyzed by linear regression.

Images